17 citations · 17 across the 1 of their papers we have counts for
2 papers
cs.LG2020★ 17 cited
SAMBA: Safe Model-Based & Active Reinforcement Learning
Alexander I. Cowen-Rivers, Daniel Palenicek, Vincent Moens +4
In this paper, we propose SAMBA, a novel framework for safe reinforcement learning that combines aspects from probabilistic modelling, information theory, and statistics. Our metho…
cs.LG2019
Wasserstein Robust Reinforcement Learning
Mohammed Amin Abdullah, Hang Ren, Haitham Bou Ammar +4
Reinforcement learning algorithms, though successful, tend to over-fit to training environments hampering their application to the real-world. This paper proposes $\text{W}\text{R}…